2026-01-29 10:23 |
[FZJ-2026-01377]
Report
Johansen ; Vaa, M. 1. O. i. ; Tabandeh, M. ; et al
Guidelines for data quality, measurement uncertainty, and traceability in sensor networks
[EPM 22DIT02 FunSNM]
As sensor networks become easier to acquire and deploy, and consequently are morecommon in almost all industries and in everyday life, so ensuring the trustworthiness andreliability of measurements and data in such systems becomes more challenging. Not onlyas the numbers of sensors grow, but also as the inaccessibility of sensors means it isinfeasible to use established methods for their calibration, so the difficulties of assessingmeasurement uncertainty in sensor networks and establishing the traceability ofmeasurements made by such systems increases. [...]
OpenAccess: PDF; External link: Fulltext
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2026-01-28 12:10 |
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2026-01-28 10:31 |
[FZJ-2026-01298]
Report
La Franca, M. ; Bosco, F. ; Carta, D. ; et al
D5.1 - Report on planning of demonstration actions across the pilot sites
[D5.1]
This comprehensive document offers an exhaustive exploration of the process involved in planning, analyzing, and executing demonstration actions across a spectrum of pilot sites. It starts by conducting a thorough examination of relevant use cases, meticulously identifying key performance indicators (KPIs), and developing robust methodologies for target setting and estimation. [...]
External link: Fulltext
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2026-01-28 10:29 |
[FZJ-2026-01297]
Report
La Franca, M. ; Lucas, A. ; Carta, D. ; et al
D4.2 - Service provision based on connected data spaces report
[D4.2]
The task 'Service Provision Based on Connected Data Spaces' aims to establish a data-sharing ecosystem that supports the creation of decentralized data models and the deployment of services and functionalities through seamless data exchange. This objective will be achieved by implementing measures to deliver a scalable, open, interoperable, and cyber-secure ICT framework driven by data. [...]
External link: Fulltext
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2026-01-28 10:27 |
[FZJ-2026-01296]
Report
Candellari, N. ; Nemček, P. ; Carta, D. ; et al
D5.2 – Report on Software Tools Integration and Test Execution Across the Pilot Sites
[D5.2]
The InterSTORE project, funded by the European Union’s Horizon Europe programme, addresses the critical challenge of integrating distributed energy resources (DERs) and storage systems into a decentralized, renewable-driven energy architecture. As Europe transitions from centralized fossil-based generation to a more flexible and resilient grid, the need for interoperable, scalable, and secure communication frameworks becomes paramount. [...]
External link: Fulltext
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2026-01-28 10:00 |
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2026-01-28 09:54 |
[FZJ-2026-01284]
Report
Rakhshani, E. ; Garcia, D. ; Gümrükcü, E. ; et al
D3.3 – Report on the Software Tool Integration with the Selected Platforms
[D3.3]
This deliverable, D3.3 – Report on the Software Tool Integration with Selected Platforms, documents the work carried out in Task T3.3 of the InterSTORE project, which focuses on the integration procedure and mapping of interoperability software tools with diverse Energy Management Systems (EMS) across multiple partner platforms. Building on the developments from WP2, where the IEEE 2030.5-based client/server library and the Legacy Protocol Converter (LPC) were designed and validated, this task translates those solutions into real-world deployments at the platform level. [...]
External link: Fulltext
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2026-01-28 09:51 |
[FZJ-2026-01281]
Report
Carta, D. ; Rakhshani, E. ; Gümrükcü, E. ; et al
D5.3 – Report on evaluation of use cases and KPIs evaluation
[D5.3]
This deliverable presents an evaluation of KPIs that provides quantitative evidence of the value created by InterSTORE. These results will inform future exploitation, replication and policy recommendations, ensuring that the project’s outcomes accelerate the transition to a decentralised, decarbonised energy system and support market adoption. It is worth noting that, according to the FAIR principle and the data management plan proce-dures of the InterSTORE project, this deliverable will be uploaded to the Zenodo repository, together with material useful for analysing the KPIs. [...]
External link: Fulltext
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2026-01-22 15:10 |
[FZJ-2026-00918]
Report
Aach, M. ; Adolph, L. ; Baumann, S. ; et al
Automotive Foundation Models: Fundamentals, Training Concepts and Applications
[Whitepaper 1]
177 p. (2025)2025
Generative AI has gained wide attention through large-scale models such as DALL-E 3, StableDiffusion, and GPT-4, creating new opportunities for innovation while raising important ethicalquestions. At the core of these advancements are foundation models: massive neural networkspretrained on extensive datasets and designed to adapt across diverse tasks and data modalities.Their ability to unify camera, LiDAR, radar, and other sensor data has significant potential forenhancing perception, prediction, and planning in autonomous driving. [...]
Restricted: PDF; External link: Fulltext
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2026-01-22 12:42 |
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